Pulse oximeter sensor with piece-wise function

ABSTRACT

A memory in a sensor is used to store multiple coefficients for a physiological parameter. In one embodiment, not only are the sensor&#39;s specific calibration coefficients stored in a memory in the sensor for the formula to determine oxygen saturation, but multiple sets of coefficients are stored. The multiple sets apply to different ranges of saturation values to provide a better fit to occur by breaking the R to SpO2 relationship up into different pieces, each described by a different function. The different functions can also be according to different formulas for determining oxygen saturation.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a divisional of U.S. application Ser. No.11/241,063, filed Sep. 30, 2005, which is a continuation of U.S.application Ser. No. 10/798,596, filed Mar. 10, 2004, now U.S. Pat. No.7,689,259, which is a continuation of U.S. application Ser. No.09/836,050, filed Apr. 16, 2001, now U.S. Pat. No. 6,801,797, whichclaims the benefit of U.S. Provisional Application No. 60/198,109, filedApr. 17, 2000, the disclosures of which are each incorporated herein byreference.

BACKGROUND OF THE INVENTION

The present invention relates to oximeter sensors having a memory.

Pulse oximetry is typically used to measure various blood flowcharacteristics including, but not limited to, the blood-oxygensaturation of hemoglobin in arterial blood, and the rate of bloodpulsations corresponding to a heart rate of a patient. Measurement ofthese characteristics has been accomplished by use of a non-invasivesensor which passes light through a portion of the patient's tissuewhere blood perfuses the tissue, and photoelectrically senses theabsorption of light in such tissue. The amount of light absorbed is thenused to calculate the amount of blood constituent being measured.

The light passed through the tissue is selected to be of one or morewavelengths that are absorbed by the blood in an amount representativeof the amount of the blood constituent present in the blood. The amountof transmitted or reflected light passed through the tissue will vary inaccordance with the changing amount of blood constituent in the tissueand the related light absorption. For measuring blood oxygen level, suchsensors have been provided with light sources and photodetectors thatare adapted to operate at two different wavelengths, in accordance withknown techniques for measuring blood oxygen saturation.

Various methods have been proposed in the past for coding information insensors, including pulse oximeter sensors, to convey useful informationto a monitor. For example, an encoding mechanism is shown in NellcorU.S. Pat. No. 4,700,708. This mechanism relates to an optical oximeterprobe which uses a pair of light emitting diodes (LEDs) to direct lightthrough blood-perfused tissue, with a detector picking up light whichhas not been absorbed by the tissue. The operation depends upon knowingthe wavelength of the LEDs. Since the wavelength of LEDs can vary fromdevice-to-device, a coding resistor is placed in the sensor with thevalue of the resistor corresponding to the actual wavelength of at leastone of the LEDs. When the oximeter instrument is turned on, it firstdetermines the value of the resistor and thus appropriate saturationcalculation coefficients for the value of the wavelengths of the LEDs inthe probe.

Other coding mechanisms have also been proposed in U.S. Pat. Nos.5,259,381; 4,942,877; 4,446,715; 3,790,910; 4,303,984; 4,621,643;5,246,003; 3,720,177; 4,684,245; 5,645,059; 5,058,588; 4,858,615; and4,942,877, the disclosures of which are all hereby incorporated byreference. The '877 patent in particular discloses storing a variety ofdata in a pulse oximetry sensor memory, including coefficients for asaturation equation for oximetry.

Nellcor pulse oximeter sensors are encoded with a resistor (RCAL) valuethat corresponds to the wavelength(s) of the LED(s) within the emitter,such as described in U.S. Pat. No. 4,700,708. Nellcor pulse oximeterinstruments read this resistor coding value and use it as a pointer to alook-up table that holds the proper set of coefficients for that sensorfor calculating arterial oxygen saturation (Sp0₂). The function thatconverts the measured red and IR signal modulation ratio R (also knownas the “ratio of ratios” or “rat-rat”) to a calculated saturation valueis derived from the basic form of the Lambert-Beer Law:

$\begin{matrix}\begin{matrix}{R = \frac{{\ln \left( {I_{1}/I_{2}} \right)}_{red}}{{\ln \left( {I_{1}/I_{2}} \right)}_{ir}}} \\{= \frac{{S \cdot \beta_{O\; 2\; {Hb}}^{red}} + {\left( {1 - S} \right) \cdot \beta_{Hb}^{red}}}{{S \cdot \beta_{O\; 2{Hb}}^{ir}} + {\left( {1 - S} \right) \cdot \beta_{Hb}^{ir}}}} \\{= \frac{{S \cdot c_{1}} + {\left( {1 - S} \right) \cdot c_{2}}}{{S \cdot c_{3}} + {\left( {1 - S} \right) \cdot c_{4}}}}\end{matrix} & (1)\end{matrix}$

where I₁ and I₂ refer to detected light signals at two different pointsin the cardiac cycle, and the β's refer to the characteristic lightabsorption properties of oxygenated and deoxygenated hemoglobin. Whensolved for the saturation (S), the result takes on the form:

$\begin{matrix}{{{Sp}O}_{2} = {{S \cdot 100} = {\frac{c_{2} - {c_{4} \cdot R}}{{\left( {c_{3} - c_{4}} \right) \cdot R} + \left( {c_{2} - c_{1}} \right)} \cdot 100.}}} & (2)\end{matrix}$

Equation 2 can be further simplified to require only three constants(by, for example, dividing each constant by c₂), but will be used asshown for the remainder of this description. Although theoreticallybased, the four constants c₁-c₄ are empirically determined. Theoreticalvalues for the constants are insufficient primarily due to thecomplexities of light scattering and sensor optics. The values of thesets of constants (c₁ through c₄) vary with each resistor coding bin(each “bin” corresponding to a range of different characterized LEDwavelengths). Multiple sets of coefficients (bins) are provided within alookup table in Nellcor oximeters. When calculated SpO₂ values accordingto Eq. 2 are less than 70%, a revised value of SpO₂ using a linearfunction is used:

SpO ₂ =c ₅ −c ₆ ·R,  (3)

where both c₅ and c₆ vary with the resistor coding value. This linearfunction was found to better match SpO₂ (arterial oxygen saturation asmeasured by a pulse oximeter) with SaO₂ (the true value of arterialoxygen saturation, as measured directly on a blood sample) inobservations made at low saturations.

A limitation of this method is that the proper calibration of the pulseoximetry sensor can be accomplished only if the relationship between thesignal modulation ratio (R) to blood SaO₂ conforms to one of thepre-encoded sets of calibration coefficients.

A further limitation of this method is that the relationship between Rand SaO₂ of the pulse oximetry sensor may not be linear in alow-saturation region, or that the breakpoint may not optimally belocated at 70% SpO₂.

A yet further limitation of this prior art method is that the functionalrelationship between the true arterial oxygen saturation and themeasured signals may not fit a single function over the entire span ofthe measurement range.

SUMMARY OF THE INVENTION

The present invention takes advantage of a memory in the sensor toprovide enhanced performance. In one embodiment, not only are thesensor's specific calibration coefficients stored in a memory in thesensor for the formula to determine oxygen saturation, but multiple setsof coefficients are stored. The multiple sets apply to different rangesof saturation values to provide a better fit to occur by breaking the Rto SpO2 relationship up into different pieces, each described by adifferent function. The different functions can also be according todifferent formulas for determining oxygen saturation.

In another aspect of the invention, the sensor can store a variablebreakpoint between the two functions used for oxygen saturation. The twofunctions could either be separate formulas or the same formula withdifferent coefficients. This allows optimization to a value other thanthe 70% breakpoint of the prior art.

In another aspect of the present invention, the sensor can store morethan one breakpoint to create more than two functions describing the Rto SpO2 relationship.

In yet another aspect of the present invention, a spline function isused, breaking up the R to SpO2 relationship into an arbitrary number ofregions.

In one embodiment, the coefficients stored in the sensor memorycorrespond to a non-linear curve for low saturation values below 70% orsome other breakpoint(s).

Each of the methods described here improve the fit between the chosenmathematical function and the arterial oxygen saturation by breaking therelationship into subsets of the full measured range and determiningoptimum coefficients for each range. Spline-fitting, in this context,similarly breaks the full measurement range into subsets to efficientlydescribe the numerical relational between the underlying tissueparameter of interest and the actual signals being used to estimate itsvalue.

For a further understanding of the nature and advantages of theinvention, reference should be made to the following description takenin conjunction with the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of a pulse oximeter system incorporating thepresent invention.

FIG. 2 is a graph of R (signal modulation ratio) versus oxygensaturation (SaO₂).

FIG. 3 is a diagram of the contents of a sensor memory according to theinvention.

FIG. 4 is a graph of oxygen saturation versus R to illustrate theembodiment for spline or curve fitting to a predefined set of knots.

FIGS. 5A, 5B, 6A and 6B are graphs illustrating the improved curvefitting of the embodiments of the invention versus the prior art.

DESCRIPTION OF THE SPECIFIC EMBODIMENTS Sensor Reader/Monitor

FIG. 1 is a block diagram of one embodiment of the invention. FIG. 1shows a pulse oximeter 17 (or sensor reader) which is connected to anon-invasive sensor 15 attached to patient tissue 18. Light from sensorLEDs 14 passes into the patient tissue 18, and after being transmittedthrough or reflected from tissue 18, the light is received byphotosensor 16. Either two or more LEDs can be used depending upon theembodiment of the present invention. Photosensor 16 converts thereceived energy into an electrical signal, which is then fed to inputamplifier 20.

Light sources other than LEDs can be used. For example, lasers could beused, or a white light source could be used with appropriate wavelengthfilters either at the transmitting or receiving ends.

Time Processing Unit (TPU) 48 sends control signals to the LED drive 32,to activate the LEDs, typically in alternation. Again, depending on theembodiment, the drive may control two or any additional desired numberof LEDs.

The signal received from input amplifier 20 is passed through twodifferent channels as shown in the embodiment of FIG. 1 for twodifferent wavelengths. Alternately, three channels for three wavelengthscould be used, or N channels for N wavelengths. Each channel includes ananalog switch 40, a low pass filter 42, and an analog to digital (A/D)converter 38. Control lines from TPU 48 select the appropriate channelat the time the corresponding LED 14 is being driven, insynchronization. A queued serial module (QSM) 46 receives the digitaldata from each of the channels via data lines 79. CPU 50 transfers thedata from QSM 46 into RAM 52 as QSM 46 periodically fills up. In oneembodiment, QSM 46, TPU 48, CPU 50 and RAM 52 are part of one integratedcircuit, such as a microcontroller.

Sensor Memory

Sensor 15, which includes photodetector 16 and LEDs 14, has a sensormemory 12 associated with it. Memory 12 is connected to CPU 50 in thesensor reader or monitor 17. The memory 12 could be packaged in a bodyof the sensor 15 or in an electrical plug connected to the sensor.Alternatively, the memory 12 could be packaged in a housing which isattachable to an external surface of the monitor or the memory 12 couldbe located anywhere in a signal path between the sensor body and themonitor. Specifically, according to some preferred embodiments, acontent of the sensor memory 12 could be constant for all sensorsassociated with a particular sensor model. In this case, instead ofputting an individual memory 12 on each sensor associated with thismodel, the memory 12 could instead be included in a reusable extensioncable associated with the sensor model. If the sensor model is adisposable sensor, in this case a single memory 12 would be incorporatedinto a reusable extension cable. The reusable cable could then be usedwith multiple disposable sensors.

FIG. 2 is an example of a graph of the ratio of ratios (R) on the X axisversus oxygen saturation (SaO₂) on the Y axis. Shown is a breakpoint 52.In the prior art, a breakpoint of 70% was pre-defined in the monitorsoftware. To the right of the breakpoint (oxygen saturations between70-100%) a formula was used with four coefficients. To the left of thebreakpoint in the prior art, a linear equation was used with twocoefficients. The present invention provides increased flexibility andaccuracy by using a non-linear formula for the portion of the curve tothe left of breakpoint 52. By using a memory chip in the sensor itself,it is possible to actually store these coefficients on the memory chip,as well as the separate coefficients for the higher saturation values.

In another embodiment of the invention, breakpoint 52 can be stored inthe memory chip, and chosen to optimize the curve fitting for the twosets of coefficients. In other words, a better fit to the two curves maybe obtained if the breakpoint is 68%, for example. In an alternateembodiment, multiple breakpoints and curves might be used. In addition,rather than using the same formula, different formulas could be used fordifferent sections in another embodiment.

FIG. 3 illustrates the contents of sensor memory 12 of FIG. 1. Asillustrated, in a first section of memory 54 are stored a first set ofcoefficients. A second portion of memory 56 stores a second set ofcoefficients. Finally, in a third section of memory 58, the breakpoint52 is stored. Different combinations of these elements could be storedin different memories. For example, the breakpoint could be left out ofsome, and in others a breakpoint may be provided with only one set ofcoefficients (with the other set of coefficients in the monitor).Alternately, a breakpoint might be implied from a sensor model numberwhich is stored in the memory, or some other ID value.

β-Equation:

In one embodiment, an enhanced form of the curvilinear function is used.Instead of using Eq.3 (linear) in the lower saturation region, Eq.2(non-linear) is used for both the upper and lower saturation regions.The breakpoint that defines when to switch coefficients from anupper-region set to a lower-region set is defined by anothercoefficient. The breakpoint can be programmed either as a value of R, oras a value of SpO₂. With the breakpoint defined as a value of R, thealgorithm becomes:

$\begin{matrix}{{{Sp}O}_{2} = {{\frac{b - {d \cdot R}}{{\left( {c - d} \right) \cdot R} + \left( {b - a} \right)} \cdot 100}\left\{ \begin{matrix}{{{R \leq {c_{5}:a}} = c_{1}},{b = c_{2}},{c = c_{3}},{d = c_{4}}} \\{{{R > {c_{5}:a}} = c_{6}},{b = c_{7}},{c = c_{8}},{d = c_{9}}}\end{matrix} \right.}} & (4)\end{matrix}$

Curve Fitting

Curve fitting to multiple regions follows the same methodology asfitting to a single region. Simply put, the data is partitioned intoseparate regions and coefficients are determined for each regionseparately. Commercially available software programs are available, (forexample, Mathcad, (Mathsoft, Inc., Cambridge, Mass.). The process canalso be found in, for example, Data Reduction and Error Analysis for thePhysical Sciences (Philip Beviyton, McGraw-Hill, New York 1969, Ch.11—Least squares fit to an arbitrary function).

Spline Fitting

An alternate embodiment uses either spline (curve) fitting, or linear orhigher order interpolation to a predefined set of SpO₂ vs R values(“knots”). A “knot” is a term of art in spline fitting that refers to anx-y pair corresponding to a node on a line, with a number of such knotsdefining the line. Spline fitting is a technique for interpolation.

For instance, the values of R at specifically defined SpO₂ values wouldbe stored in the sensor memory. An example of this looks like:

$R = \begin{matrix}a & b & c\end{matrix}$ ${{Sp}O}_{2} = \begin{matrix}100 & 95 & 90\end{matrix}$

Alternatively, though less preferably, the independent variable could beswapped:

$R = \begin{matrix}0.5 & 0.6 & 0.7\end{matrix}$ ${{Sp}O}_{2} = \begin{matrix}x & y & z\end{matrix}$

-   a) Only the bold values (e.g., a, b and c) would need to be stored    with fixed, pre-selected spaced values of SpO₂ (equally spaced or    unequally spaced). Or, alternatively, preselected values of R.-   b) An alternative approach would store within the sensor memory the    SpO₂(minimum) and SpO₂(maximum) values of the spline range, the    number of knots that will be defined, and the sequence of defined    values of R for those knots.-   c) A further alternative approach could store both SpO₂ and the    associated R value for each knot.    For each of these options, the instrument would use a spline-fitting    algorithm, preferably a cubic spline, to determine the SpO₂ at the    measured value of R according to the stored values (an alternative    could be a linear or higher order interpolation algorithm).

FIG. 4 illustrates the cubic spline method. FIG. 4 is a graph of oxygensaturation vs. R for a particular sensor emitter. Thus, instead ofstoring the coefficients as in the prior art method, the actual R oroxygen saturation values are calculated and stored in the sensor memoryfor that particular sensor's characteristics (e.g., emitterwavelengths). When the oximeter measures the signal level of the lightdetector, it determines an oxygen saturation value by determining thepoint on the curve associated with the calculated R value between two ofthe sample points shown in FIG. 4.

There exists a trade-off in the number of knots defined and the amountof memory required to store them. Too few knots requires very littlestorage memory, but may not adequately describe the functionalrelationship; too many over-defines the curve and consumes more memory.The inventors have found that knots spaced 5%-10% apart give adequateresults.

Cubic Spline Calculation:

The process for cubic spline interpolation is known to those skilled inthe art. Intrinsic in using the spline method is that the value of Rneeds to be determined first before being translated to SpO₂. Thepreferred process for spline interpolation can be accomplished using thefunctions provided in Mathcad, and treats the endpoints with cubicfunctions. Other references for cubic spline interpolations areavailable.

The process of finding the coordinates of the knots in empirical datawith a significant amount of noise may require an additional step.Commercially available basic curve fitting programs may be used(sigmaPlot, or TableCurve, or Mathematical for instance) to determine abest-fit functional approximation to the data. Alternately, one canperform a least-squares fit of an arbitrarily chosen analytical functionand pick the values of R at the knot locations (SaO₂ values). Theanalytical function can be an overlapping piece-wise polynomial (e.g.,linear or parabolic), or the curvilinear equation of Eq. 1 or Eq. 4.Another approach is to perform a least-squares selection of the knotsdirectly.

FIG. 5A shows the conventional curve fitting of the prior art, wherein alinear relationship is used below 70% saturation, with a curvilinearapproach above 70%. The residual error due to an imperfect fit to theactual R to Sa0₂ response for the curvilinear approach above 70%saturation is illustrated by curve 60, while the residual error of thelinear interpolation approach below 70% is illustrated by dots 62. FIG.5B illustrates the use of curvilinear fits in both regions, with adifferent curvilinear curve 64 being used below 70%. In this instance, amuch improved fit is provided. In both figures, the smaller dotted line66 corresponds to the use of a single curvilinear fit across bothregions, which is also not as accurate, having a much higher errorcharacteristic compared to the curves of the invention, 64 and 60 ofFIG. 5B.

FIGS. 6A and 6B show a plurality of knots as circles 70 on the graphs.Dotted line 72 of FIG. 6A illustrates a linear interpolation fit tothese knots, which shows a residual error prone result with multipleloops. In FIG. 6B, on the other hand, the present invention using acubic spline fitting approach provides a dotted line 74 which is a moreaccurate fit to the knots 70.

As will be understood by those of skill in the art, the presentinvention may be embodied in other specific embodiments withoutdeparting from the essential characteristics thereof. For example, anyfunction can be used for the formulas for determining oxygen saturation,not just the ones described. For a limited sensor memory, the functionrepresentation may be compressed. Any representation of a function couldbe used. Calibration coefficients may be based on more or differentcharacteristics than the sensor's LED wavelength(s). For example, otherLED emitter characteristics or sensor design characteristics can befactors in the sensor's calibration coefficients.

Additionally, the formula for calculating oxygen saturation may be afunction of more than the ratio of ratios; for example, other inputvariables such as signal strength, light levels, and signals frommultiple detectors could be used.

This methodology for piece-wise fitting is not limited to oximetry. Thismethod is useful when the relationship between the measured signal andreference value observed during calibration is not adequately describedby a single function or set of coefficients over the whole measurementrange. The relationship may be broken into subsets, and a piece-wisecontinuous set of functions may be used to describe the relationship.For example, other blood or tissue constituents could be calculated,such as carboxyhemoglobin, methemoglobin, bilirubin, glucose, lactate,etc. Accordingly, the foregoing description is intended to beillustrative, but not limiting, of the scope of the invention which isset forth in the following claims.

What is claimed is:
 1. A method of manufacturing an oximeter system,comprising: providing a memory of an oximeter sensor having coefficientsstored therein, the coefficients for use in at least one formula fordetermining oxygen saturation, the coefficients including at least afirst set of coefficients and a second set of coefficients for a lightemitter, wherein the first and second sets of coefficients are for usein different formulas.
 2. The method of claim 1, wherein the differentformulas comprise different linear formulas.
 3. The method of claim 1,wherein the different formulas comprise different non-linear formulas.4. The method of claim 1, wherein at least one of the different formulascomprises a spline function or a ratio-of-ratios function.
 5. A methodof operating an oximeter sensor, comprising: directing light at apatient with a light emitter; receiving the light from the patient witha light detector; and transmitting coefficients from a memory of theoximeter sensor to a monitor, the coefficients for use in at least oneformula for determining oxygen saturation, the coefficients including atleast a first set of coefficients and a second set of coefficients forthe light emitter, wherein the first and second sets of coefficients arefor use in different formulas.
 6. The method of claim 5, wherein thedifferent formulas comprise different linear formulas.
 7. The method ofclaim 5, wherein the different formulas comprise different nonlinearformulas.
 8. The method of claim 5, wherein at least one of thedifferent formulas comprises a spline function or a ratio-of-ratiosfunction.
 9. An oximeter system, comprising: an oximeter sensor,comprising: a light emitter configured to direct light at a patient; alight detector configured to receive the light from the patient; and amemory storing coefficients, the coefficients including at least a firstset of coefficients and a second set of coefficients for the lightemitter, wherein the first and second sets of coefficients are for usein different formulas for determining oxygen saturation; an oximetermonitor, comprising: a drive circuit configured to provide signals tothe oximeter sensor; and a read circuit configured to read thecoefficients from the memory of the oximeter sensor.
 10. The oximetersystem of claim 9, wherein the different formulas comprise differentlinear formulas.
 11. The oximeter system of claim 9, wherein thedifferent formulas comprise different nonlinear formulas.
 12. Theoximeter system of claim 9, wherein at least one of the differentformulas comprises a spline function or a ratio-of-ratios function. 13.An oximeter monitor, comprising: a drive circuit configured to providesignals to an oximeter sensor that is coupleable to a patient; a readcircuit configured to receive coefficients from a memory of the oximetersensor, the coefficients including first and second sets of coefficientsfor a light emitter of the oximeter sensor; and a calculation mechanismconfigured to utilize the first and second sets of coefficients indifferent formulas to determine a blood oxygen saturation level of thepatient.
 14. The oximeter monitor of claim 13, wherein the differentformulas comprise different linear formulas.
 15. The oximeter monitor ofclaim 13, wherein the different formulas comprise different nonlinearformulas.
 16. The oximeter monitor of claim 13, wherein at least one ofthe different formulas comprises a spline function or a ratio-of-ratiosfunction.
 17. A method of monitor operation, comprising: providingsignals to circuitry of an oximeter sensor that is coupleable to apatient; receiving information from a memory of the oximeter sensor, theinformation comprising first and second sets of coefficients for a lightemitter of the oximeter sensor; and utilizing the first and second setsof coefficients in different formulas to determine a blood oxygensaturation level of a patient.
 18. The method of claim 17, wherein thedifferent formulas comprise different linear formulas.
 19. The method ofclaim 17, wherein the different formulas comprise different nonlinearformulas.
 20. The method of claim 17, wherein at least one of thedifferent functions comprises a spline function or a ratio-of-ratiosfunction.